Current attempts to control the shear amount, the digital manipulation, the aggregation, and the dissemination of sensitive personal information stored across computer-implemented social network site storage networks are resource, energy, and time consuming. These attempts consume resources, energy, and time—on all three of individual, organizational and large-and-mega-scale digital computer server and non-server networks.
Some advocate abstinence or discontinued use, which negates the technological advantages of social network site computer networks.
Others suggest sacrificing security by allowing all information to proliferate without reservation or with minimal reservation, which causes an overabundance of distributed content.
Still others teach identification management by identifying Facebook® and Twitter® content containing text (e.g., profanity) or objects in photos (e.g., beer cans), which have been previously defined in a blacklist. Blacklist techniques suffer from several problems such as the inability to technically scale them for network-wide use, such that large volumes of data cannot be managed. They also lead to false positives, wherein valued objects are unduly deleted.
On an individual scale, it is estimated that, for example, an average Facebook user account stores nearly 8500 new data objects per year, which it is estimated would take more than two days to identify and delete on an item-by-item basis assuming that it takes about 5 seconds to identify and remove each object.
It would be desirable to provide a more effective method of creating more efficient digital privacy management, which would reduce the storage space required to store, the bandwidth to aggregate and calculate, and/or the computing resources, time, and energy previously required, especially as regarding management of redundant and private, sensitive personal data.